The recent version requires images of a lateral position. It is important that the position is precise since deviation may confound with feature annotations. Images from any source can be used. However, depending on the image properties parameters may have to be adjusted. Furthermore, images obtained with normal microscope and not using an automated position system with embryos in glass capillaries require conversion using a KNIME workflow (the workflow is available as well). As a result of the analysis the software provides JSON files that contain the coordinates of the features. Coordinates are provided for eye, fish contour, notochord , otoliths, yolk sac, pericard and swimbladder. Furthermore, pigment cells in the notochord area are detected. Additional features can be manually annotated. It is the aim of the software to provide the coordinates, which may then be analysed subsequently to identify and quantify changes in the morphology of zebrafish embryos.

It is slightly different from the methods described in the paper itself, where the method was to work on a maximum intensity projection of a 3D-SIM stack, and then to fit circle to the centrioles to estimate the diameters of the toroids.

In this workflow, the images are read from the IDR , then process by thresholding (Maximum entropy auto thresholding with Image J), and processed by Analyze Particles with different measurement sets, including the bouding box. Then the analysis of diameters and the statistical test are performed using R. All the code and data sets are available, and in the case of this paper have shown a layered organisation of the proteins.

hIPNAT

hIPNAT (hIPNAT: Image Processing for NeuroAnatomy and Tree-like structures) is a set of tools for the analysis of images of neurons and other tree-like morphologies. It is written for ImageJ, the de facto standard in scientific image processing. It is available through the ImageJ Neuroanatomy update site.

MorphoLibJ

MorphoLibJ is a library of plugin for ImageJ with functionalities for image processing such as filtering, reconstructing, segmenting, etc... Tools are based on Mathematical morphology with more rigorous mathematical approach than in the standard tools of ImageJ in particular for surface (or perimeter) measurements which are usually based on voxel counting.

Microscope Image Correlation Spectroscopy MICS

Fluorescence spectroscopy by image correlation is a technique that allows analysing and characterizing the different molecular dynamics from a sequence of fluorescence images. Many image correlation techniques have been developed for different applications but in particular to study the mechanisms of cell adhesion during migration. These techniques can be used with most imaging modalities: e.g. fluorescence widefield, confocal microscopy, TIRFM. They allow to obtain information such as the density in molecules, diffusion coefficients, the presence of several populations, or the direction and speed of a movement corresponding to active transport when spatial and temporal correlations are taken into account (STICS: Spatio-Temporal Image Correlation Spectroscopy). Please see 2580 for a review and the description of the methods. This plugin is based on ICS_tools plugin by Fitz Elliott, available [here](http://www.cellmigration.org/resource/imaging/imaging_resources.shtml "cell migration website"). Some bugs have been removed, ROI does not need to be squared, fitting is weighted in order to give more weight to the smaller lags (temporal or spatial) Exemple of use on sample data [fluorescent beads](http://biii.info/node/2577 "Beads") - Select an ROI, start by ICS to get the right PSF size - Then run TICS and select diffusion, or diffusion plus flow model. Remove the first line (autocorrelation) which corresponds to the noise autocorrelation before fitting.

ilastik

ilastik is a simple, user-friendly tool for interactive image classification, segmentation and analysis. It is built as a modular software framework, which currently has workflows for automated (supervised) pixel- and object-level classification, automated and semi-automated object tracking, semi-automated segmentation and object counting without detection. Most analysis operations are performed lazily, which enables targeted interactive processing of data subvolumes, followed by complete volume analysis in offline batch mode. Using it requires no experience in image processing.

ilastik (the image learning, analysis, and segmentation toolkit) provides non-experts with a menu of pre-built image analysis workflows. ilastik handles data of up to five dimensions (time, 3D space, and spectral dimension). Its workflows provide an interactive experience to give the user immediate feedback on the quality of the results yielded by her chosen parameters and/or labelings.

The most commonly used workflow is pixel classification, which requires very little parameter tuning and instead offers a machine learning technique for segmenting an image based on local image features computed for each pixel.

Other workflows include:

Object classification: Similar to pixel classification, but classifies previously segmented objects by object characteristics in a subsequent step

Autocontext: This workflow improves the pixel classification workflow by running it in multiple stages and showing each pixel the results of the previous stage.

3D Objects Counter

3D intensity related measurement (with possible redirection to an image with the actual intensity value to be measured, for example for two channels measurements)

Volume and shape factors measurements, surface etc...

generates results representations such as:

Objects' map;

Surface voxels' map;

Centroids' map;

Centres of masses' map.

As ImageJ's “Analyze Particles” function, 3D-OC also has a “redirect to” option, allowing one image to be taken as a mask to quantify intensity related parameters on a second image. But unlike the Analyze particle, it include a thresholding option, meaning that you can start from a gray level stack, not necessarily a binary mask.

To use it, first set the list of measurements by editing 3D OC Options. Both (3D Object counter and 3D OC Options are now in the default Fiji "Analyze" menu.

ROI Statistics

This tool compute measures on the ROIs of the chosen sequence, updates the measures live when ROIs are changed and allows to copy/paste the measures to 3rd-party sheet edition softwares. Measures include geometric (bounding box) and intensity information.

It can complement the default ICY built inROI table, where measurements such as volume meausirements, intensity measurements, ... are built in and can be exported as excel as well.